The role of acute changes in mBDNF, cortisol and pro-BDNF in predicting cognitive performance in old age

The interplay between biomarkers of relevance to neuroplasticity and its association with learning and cognitive ability in old age remains poorly understood. The present study investigated acute changes in plasma concentrations of mature brain-derived neurotrophic factor (mBDNF), its precursor protein (pro-BDNF), and cortisol, in response to acute physical exercise and cognitive training interventions, their covariation and role in predicting cognitive performance. Confirmatory results provided no support for mBDNF, pro-BDNF and cortisol co-varying over time, as the acute interventions unfolded, but did confirm a positive association between mBDNF and pro-BDNF at rest. The confirmatory results did not support the hypothesis that mBDNF change following physical exercise were counteracted by temporally coupled changes in cortisol or pro-BDNF, or by cortisol at rest, in its previously demonstrated faciliatory effect on cognitive training outcome. Exploratory results instead provided indications of a general and trait-like cognitive benefit of exhibiting greater mBDNF responsiveness to acute interventions when coupled with lesser cortisol responsiveness, greater pro-BDNF responsiveness, and lower cortisol at rest. As such, the results call for future work to test whether certain biomarker profiles are associated with preserved cognition in old age.

www.nature.com/scientificreports/ a baseline measure, reflecting biomarker concentrations at rest. Participants subsequently commenced with 35 min of cognitive training or 35 min of physical exercise, depending on the randomly allocated intervention, after which the second sample was immediately collected. Participants then engaged in 35 min cognitive training, 35 min physical exercise or 35 min seated rest, also depending on intervention, after which the third sample was drawn. Thus, a total of six blood samples were drawn from each participant, three at pretest (Sample 1-3) and three at posttest (Sample 4-6). To avoid contamination and clotting between samples, the catheter was flushed with saline solution between each draw. The blood sampling session was always scheduled for the first half of the day, starting at 7:45, 09:15 or 10:45, with the first blood sample being drawn at 08:00, 09:30 or 11:00. The timing was kept the same for each participant at pre-test and post-test and was counterbalanced so that each blood sampling session started at the same average time for the four intervention groups. Participants were instructed not to consume alcohol or engage in any physical training 24 h before blood sampling, and to not eat or drink anything 2 h before blood sampling. Participants were also required to record their breakfast at pretest and were instructed to have the same breakfast at posttest. For each sample, 10 mL was collected into heparinized tubes. The blood was spun at 4 °C for 3 min at 6000 rpm to separate the plasma, which was transferred to Eppendorf tubes and frozen at − 80 °C until analysis. mBDNF concentrations were quantified with samples in duplicate using enzyme-linked immunosorbant assay (ELISA) according to the manufacturer's instructions (Human BDNF Quantikine Immunoassay, DBD00, R & D Systems). Plasma levels of cortisol (ng × ml −1 ) were determined in duplicates using an ELISA Cortisol kit (#CO368S, Calbiotech, CA, USA). Plasma levels of proBDNF (pg × ml −1 ) were quantified using the Human Pro-BDNF DuoSet ELISA kit (DY3175) combined with the DuoSet Ancillary Reagent Kit 2 (DY008) from R&D Systems (MN, USA). Assays were run according to the manufacturer's instructions with minor modifications and with samples analyzed in duplicates. The modifications included sample and standard incubation over night at 4 °C instead of two hours at room temperature, as well as standard dilution in 10% fetal bovine serum supplemented with 0.01% Tween-20 instead of the supplied diluent, which was done in order to reduce background signal in the assay.
Cognitive training outcome. In the original investigation, cognitive training outcome was assessed using 18 cognitive tests at pretest and posttest, selected to systematically vary in similarity to the cognitive training tasks, which targeted the updating construct of working memory 25 . In the original study, the hypothesized closer relationship between exercise-induced increases in mBDNF and cognitive training outcome when cognitive training was preceded, as opposed to followed by physical exercise, was found only for the cognitive composite that captured performance on trained updating working memory tasks with untrained stimuli. Since the hypotheses pertaining to cognitive training outcome in the present study built directly on this finding, the same trained working memory tasks were used as the measure of cognitive training outcome for hypothesis testing (H6-H8). As such, the used cognitive composite was based on one n-back task and one running span task, both of which targeted the updating construct of working memory and were part of the cognitive training program, but with a different set of stimuli. In the n-back task, stimuli were presented one by one and participants had to press a button whenever the stimulus was the same as the one presented N steps back in the series. In the running span task, stimuli were also presented one by one and when stimuli presentation stopped, participants had to select the last N stimuli from a set of options, in the right order. More detailed descriptions of all the cognitive tests can be found in the supplementary materials of the original publication 25 .
For exploratory purposes, specifically to test generalizability of results beyond the single cognitive composite used for hypothesis testing, the remaining tasks that targeted the updating construct of working memory were used, contributing to two additional cognitive composites. The first composite was based on the exact n-back and running span tasks that were part of the cognitive training program (with identical stimuli), and the second composite was based on a numerical updating task and a spatial updating task that was not part of the cognitive training. In the numerical updating task, four digits were presented briefly before they disappeared and participants were required to perform eight mathematical updating operations on the digits kept in working memory. In the spatial updating task, three 3 × 3 grids were presented. Three dots were presented briefly, one in each grid, before they disappeared and participants were required to perform spatial shifting operations on the locations kept in working memory. Figure 1. Blood sampling protocol. Acute changes in biomarkers concentrations were measured before and after the 12-week intervention period. Blood was drawn immediately before and after the first intervention, and immediately after the second intervention or after seated rest, at pretest (samples 1-3) and at posttest (samples [4][5][6]. COG cognitive training only, PE physical exercise only, COG + PE cognitive training and then physical exercise, PE + COG physical exercise and then cognitive training. participants for all biomarkers. For mBDNF and pro-BDNF, concentrations were severely skewed at all sampling timepoints (skewness > 3.0, kurtosis > 10.0). For cortisol, concentrations were not normally distributed at the four first timepoints (skewness > 3.0 and/or kurtosis > 10.0). Natural log-transformations were therefore performed for all biomarker concentrations at all timepoints, which resulted in approximate normality for all measures (skewness < 3.0, kurtosis < 10.0). Extreme outliers were subsequently removed using the outlier labelling rule (IQR = 3.0), resulting in exclusion of one measurement for mBDNF, three for pro-BDNF, and one for cortisol. Repeated-measures ANOVA, with Time (pretest, posttest) and Sample (1-3) as within-subject factors and Intervention (COG, PE, COG + PE, PE + COG) as between-subject factor, was performed for each biomarker for descriptive purposes at the group level (Jamovi, version 1.6.23.0). Significant main effects were only reported and interpreted in the absence of significant interactions.
Area under the curve for biomarker change. For hypotheses 1-5, acute change in biomarker concentration over the three sampling timepoints, at pretest and at posttest, were expressed as the area under the curve with respect to change (AUC), as put forward by Pruessner, Kirschbaum 28 . As such, AUC were derived from the trapezoid formula in reference to the first value, ignoring the distance from zero for all timepoints, thereby emphasizing the changes over time. In contrast to change scores, AUC allows measurements from all three timepoints to be comprised in a single measure and was therefore selected for capturing change in biomarker concentration as the acute interventions unfolded. As such, AUC can be said to capture overall biomarker propensity to change in response to the acute interventions. AUC were calculated for mBDNF (mBDNF AUC ), pro-BDNF (Pro-BDNF AUC ) and cortisol (Cortisol AUC ), at pretest and posttest, for participants in all four intervention conditions. All AUC variables were approximately normally distributed (skewness < 3.0, kurtosis < 10.0), without extreme outliers (outlier labelling rule, IQR = 3.0).
Change scores for biomarker change. For hypotheses 6-8, which built directly on our previous findings 25 , change scores were calculated to arrive at a measure of acute biomarker change following physical exercise in the groups that received both physical exercise and cognitive training (PE + COG, COG + PE). The concentration measured before exercise was subtracted from the concentration measured immediately after. For the group with exercise as their first intervention (PE + COG), sample 1 was therefore subtracted from sample 2, and for the group with exercise as their second intervention (COG + PE), sample 2 was subtracted from sample. 3. Change scores representing acute change following physical exercise were calculated for mBDNF (mBDNF EX ), pro-BDNF (Pro-BDNF EX ) and cortisol (Cortisol EX ).
Cognitive composite. The cognitive composite used for hypothesis testing (trained tasks, untrained stimuli) was created by taking the unit-weighted average of the two tasks, at pretest and posttest, and composite scores were subsequently standardized by pretest performance ((x-mean pretest )/sd pretest ) and converted into T scores (mean pretest = 50, sd pretest = 10). The same procedure was followed for the cognitive composites that were used for exploratory analyses. All three cognitive composite was approximately normally distributed at pretest and posttest (skewness < 3.0, kurtosis < 10.0).
Linear mixed-effect modelling. Linear mixed-effects models (LMM) were used to test the hypotheses. LMMs were fitted using the lme4 package (version 1.1-26) in the R programming environment (version 4.0.4) employing restricted maximum likelihood (REML) to estimate the parameters. Inferential analyses were performed using the lmerTest package (version 3.1-3) using the Satterthwaite's approximation to estimate denominator degrees of freedom for F statistic and to obtain p-values. In all models, Time (pretest, posttest) was included as a fixed effect and Subject (intercept) as a random effect. An alpha-level of 0.05 was used to determine significance. The specific details of the statistical models are presented in the result section.

Results
Results are reported in the following order: (1) descriptive results of change in biomarker concentrations at the group level, (2) confirmatory results relating to the hypotheses and (3) selected exploratory analyses of relevance to H6-H8. For the purpose of brevity, some statistics are included in the supplementary materials (SM1-SM14). Including time of blood sampling (08:00, 9:30, 11:00) as a covariate did not change the outcome of any of the confirmatory analyses.
Descriptive results. The study sample consisted of 50 women and 43 men with an average age of 70.41 years (SD = 2.93). A majority (67) had university education, and the remainder high school (16) or elementary school education (9), with education information missing for one participant. 18 participants completed the COG intervention, 26 the PE intervention, 24 the COG + PE intervention, and 25 the PE + COG intervention. All participants were retired and were therefore not working night shifts. One participant had diabetes Type II, which was controlled with Metformin and Novonorm. All participants were non-smokers. Note that the study sample in the present study, which included only those participants who consented to the extended blood analysis, differed slightly from our previous reports of plasma mBDNF concentrations in the original study 25,27 .
To allow for a qualitative comparison of acute changes in the three studied biomarkers, based on the same study sample, descriptive results for mBDNF were therefore reported anew. Transformed concentrations for mBDNF, cortisol and pro-BDNF, at the three sampling timepoints at pretest and posttest revealed different qualitative patterns of change ( Fig. 2; for mean concentrations in original units, see SM-1). For mBDNF, there was a significant interaction between Time (pretest, posttest) and Sample (1-3, 4-6), F(2) = 6.27, p < 0.001, reflecting a steeper increase at pretest than at posttest (for estimated marginal means for significant ANOVA results, see SM-1). The interaction between Intervention (PE + COG, COG + PE, PE, COG) and Time was also significant, F(3) = 2.96, p = 0.037, reflecting differential decreases from pretest to posttest in the intervention groups. For cortisol, the interaction between Sample and Intervention was statistically significant, F(6) = 2.41, p = 0.029, reflecting an apparent pattern of increases in cortisol following physical activity but not following cognitive training. For pro-BDNF, only the main effect of Sample was significant, F(2) = 6.18, p < 0.001, reflecting a weakly increasing pattern. As such, mBDNF and pro-BDNF appear to have increased within the session, independent of intervention, whilst cortisol increased primarily following physical activity.
Confirmatory results. No support was found for H1-H4, and these hypotheses were not followed up in exploratory analyses. For the sake of brevity, these model descriptions and results are therefore presented in the supplementary materials (SM-2, SM-3, SM-4, SM-5). Below we provide model descriptions and confirmatory results for H5-H8.
Plasma pro-BDNF and plasma mBDNF are positively associated at rest (Hypothesis 5). For H5, mBDNF REST acted as dependent variable, and Time and pro-BDNF REST was entered as fixed effects, allowing for interaction with Time, adjusting for adjusting for age, sex and education. The regression coefficient for pro-BDNF REST predicting mBDNF REST  Acute changes in plasma cortisol following physical exercise counteract the beneficial effect of temporally coupled changes in plasma mBDNF for cognitive training outcome, when physical exercise precedes but not when it follows cognitive training (Hypothesis 6). Hypotheses that concerned the influence of exercise-induced changes in biomarker concentrations on cognitive training outcome built directly on previous results (H6-H8). As such, all three models were based on the previously reported model, in which the cognitive composite was the dependent variable, and Time (pretest, posttest), Intervention (COG + PE, PE + COG) and acute change in mBDNF following physical exercise (at pretest) were entered as fixed effects. As such, the fixed effect of Time in this model reflects change in the cognitive composite from pretest to posttest, referred to as cognitive training outcome.
For H6, Cortisol EX was added as a fourth fixed effect, allowing for all interactions. Support for H6 would be derived from a significant four-way interaction, by which less Cortisol EX was related to a stronger association between mBDNF EX and the cognitive composite, when physical exercise preceded but not when it followed cognitive training. In other words, the two intervention groups were expected to differ more in regards to the strength of the association between mBDNF change and cognitive training outcome when Cortisol EX was small compared to large. A significant interaction between Time and Intervention, when mBDNF EX and Cortisol EX are controlled for, would reflect alternative support for the overarching hypothesis that counteracting biomarker effects prevented a beneficial effect of physical exercise preceding cognitive training from emerging at the group level in the original investigation.
The four-way interaction between mBDNF EX, Cortisol EX , Time and Intervention (COG + PE, PE + COG), in predicting cognitive performance was not significant, F(1, 40) = 0.07, p = 0.79, providing no support for the hypothesis. The interaction between Time and Intervention was also not significant, F(1, 40) = 1.84, p = 0.18, providing no alternative support for the hypothesis. The previously reported three-way interaction between mBDNF EX, , Time and Intervention 25 , remained significant also when Cortisol EX was included in the model, F(1, 40) = 9.07, p < 0.01. No other significant interactions were found. For complete result output see SM-7.
Acute changes in plasma pro-BDNF following physical exercise counteract the beneficial effect of temporally coupled changes in plasma mBDNF for cognitive training outcome, when physical exercise precedes but not when it follows cognitive training (Hypothesis 7). The model for H7 and its interpretation was identical to that of H6, except that Pro-BDNF EX was added as a fixed effect together with Time (pretest, posttest), Intervention (COG + PE, PE + COG) and acute change in mBDNF following physical exercise (at pretest). The four-way interaction between pro-BDNF EX, m BDNF EX , Time and Intervention (COG + PE, PE + COG), in predicting cognitive performance was not significant, F(1, 40) = 0.81, p = 0.38, providing no support for the hypothesis. The previously reported three-way interaction between mBDNF EX. Time and Intervention, remained significant also when pro-BDNF EX was included in the model, F(1, 40) = 7.32, p = 0.01. An incidental three-way interaction was detected between pro-BDNF EX, m BDNF EX and Intervention, F(1, 40) = 4.99, p = 0.03, reflecting better cognitive performance when greater increases in mBDNF were coupled with greater increases in pro-BDNF following acute exercise, but only when physical exercise preceded cognitive training (Fig. 3). The effect did not differ at pretest and posttest, reflecting that coupling of greater increases of mBDNF and pro-BDNF was for cognitive performance in general and not for cognitive training outcome per se. No other interactions were found, including no significant interaction between Time and Intervention, F(1, 40)  www.nature.com/scientificreports/  Exploratory analyses. Area under the curve as an alternative measure of acute biomarker change. Since hypotheses 6-8 expanded on previous findings, confirmatory analyses involved the previously used measure of acute change in biomarker concentrations following physical exercise, namely change scores. In a set of exploratory analyses, AUC was used to instead capture biomarker propensity to change across the entire session, as in the confirmatory analyses relating to H1-H5. The aim of these analyses was to explore whether this alternative measure of change may reveal different interactive effects between biomarkers on cognitive training outcome. The same linear mixed effect models were used as for testing hypotheses 6-8, with the exceptions that AUC was used instead of change scores and models were adjusted for age, sex and education. The four-way interaction between mBDNF AUC, Cortisol AUC , Time and Intervention (COG + PE, PE + COG), in predicting cognitive performance was not significant, F(1, 39) = 1.37, p = 0.25. However, the two-way interaction between mBDNF AUC and Cortisol AUC was significant, F(1, 36) = 13.53, p < 0.001, reflecting better cognitive performance when greater mBDNF increases were coupled with lesser cortisol increases (Fig. 4A). Furthermore, the two-way interaction between Intervention (COG + PE, PE + COG) and Time (pretest, posttest) was nearsignificant, F(1, 39) = 3.54, p = 0.067, but this result likely reflect a regression to the mean rather than greater cognitive improvements in the PE + COG group (SM-10). No other significant interactions were found.
The outcome of the exploratory analyses can be summarized as indicating that acute changes in mBDNF across the entire session interacted with parallel changes in cortisol and pro-BDNF, and with cortisol at rest, in their association with the cognitive composite ( Fig. 4A-C). As such, a different set of biomarker interactions were Figure 3. Interaction between changes in mBDNF and pro-BDNF following acute physical exercise, and intervention group, on cognitive performance. Model-implied values illustrating the differential interaction between acute changes in mBDNF and pro-BDNF following physical exercise on cognitive performance (updating working memory, trained tasks with untrained stimuli), collapsed across pre-test and post-test, in the intervention group that received physical exercise before cognitive training (PE + COG) and the group that received the interventions in the reverse order (COG + PE). Shaded areas reflect 95% confidence intervals. Blue reflects the model-implied mean for pro-BDNF change, and red and green reflect one standard deviation below and above the mean, respectively. www.nature.com/scientificreports/ indeed detected using area under the curve to capture biomarkers change across the entire session, compared to when using change scores to capture change following physical exercise.
Generalizability to other working memory composites. When testing hypothesis 7, an incidental interaction reflected better cognitive performance when greater increases in mBDNF were coupled with greater increases in pro-BDNF following acute exercise, but only when physical exercise preceded cognitive training. This result was found using a cognitive composite that captured performance on working memory tasks that were trained during the intervention period, with the exception that the stimuli was different, as motivated by previous findings on this particular composite 25 . To explore the generalizability of the finding beyond this single composite, analyses were repeated for the two other composites that also targeted the updating working memory: trained working memory task with trained stimuli, and, untrained working memory tasks. The results showed that the three-way interaction was near-significant for trained working memory tasks with trained stimuli, F(1,40) = 3.95, p = 0.054, and significant for untrained working memory tasks, F(1,40) = 4.55, p = 0.039, with both interactions following the same pattern of better cognitive performance when greater increases in mBDNF were coupled with greater increases in pro-BDNF following acute exercise, but only when physical exercise preceded cognitive training . No other interactions were significant. The same test of generalizability beyond the single cognitive composite was performed for the exploratory set of AUC analyses reported on in the previous section. The two-way interaction between mBDNF AUC and Cortisol AUC was significant for trained working memory tasks with trained stimuli, F(1, 36) = 17.29, p < 0.001, and for untrained working memory tasks, F(1, 36) = 8.89, p = 0.005, with both following the previously detected pattern of better cognitive performance for greater mBDNF increases coupled with lesser cortisol increases (SM-12). The two-way interaction between mBDNF AUC and pro-BDNF AUC was significant for trained working memory tasks with trained stimuli, F(1, 36) = 6.25, p = 0.017, following the previously detected pattern of better cognitive performance for greater mBDNF increases coupled with greater pro-BDNF increases (SM-13). However, this two-way interaction was not significant for untrained working memory tasks, F(1, 36) = 2.00, p = 0.166. The twoway interaction between mBDNF AUC and Cortisol REST was significant for trained working memory tasks with trained stimuli, F(1, 36) = 6.35, p = 0.016, and for untrained working memory tasks, F(1, 36) = 6.92, p = 0.012, both following the previously detected pattern of reflecting better cognitive performance for greater mBDNF increases coupled with lower resting cortisol . No other interactions were significant.

Discussion
By expanding the biomarker analysis of an already completed randomized-controlled trial in healthy older adult 25 , the present study investigated plasma concentrations of mBDNF, pro-BDNF, and cortisol, at rest and in response to acute interventions, as well as their role in predicting cognitive performance. The results confirmed the hypothesized positive association between mBDNF and pro-BDNF at rest, but did not give support for co-variation among acute changes in mBDNF, pro-BDNF and cortisol. The confirmatory results did also not support the hypothesis that faciliatory effects of mBDNF on cognitive training outcome were counteracted by temporally coupled changes in cortisol or pro-BDNF, or by cortisol at rest. Exploratory results instead revealed greater general cognitive performance when greater acute mBDNF responsiveness was coupled with lesser cortisol responsiveness, greater pro-BDNF responsiveness, and lower cortisol at rest. Below, we discuss the results related to each of the three study aims in more detail.
The first aim was to describe patterns of change in cortisol and pro-BDNF concentrations in blood plasma under conditions of physical exercise and cognitive training. Relative to changes in mBDNF, cortisol and , and between acute change in mBDNF and cortisol at rest (C), on cognitive performance (updating working memory, trained tasks with untrained stimuli), collapsed across pre-test and post-test. Acute changes are expressed as area under the curve with respect to change (AUC). Shaded areas reflect 95% confidence intervals. Blue reflects the model-implied mean for cortisol/pro-BDNF change, and red and green reflect one standard deviation below and above the mean, respectively. www.nature.com/scientificreports/ pro-BDNF demonstrated qualitatively different patterns of change at the group level. Whilst mBDNF and pro-BDNF in plasma both displayed gradual acute increases, independent of intervention, such increases appeared less robust for pro-BDNF. In view of previous reports of no change in serum pro-BDNF following acute physical exercise in younger adults (Inoue et al., 2020;Piepmeier et al., 2019), it can be speculated that the acute pro-BDNF response may be different in older adults. Relative to mBDNF and pro-BDNF, which both displayed acute change independent of intervention, cortisol instead appeared to increase primarily following physical exercise, which is consistent with previous reports of increases in plasma cortisol following exercise in younger adults 18 . In contrast, cognitive training was not followed by acute cortisol increases, instead there were indications of decreases, possibly due to recovery from stress induced by the blood sampling. Relative to social psychological stress, which is known to result in a strong cortisol response 29 , cognitive training therefore appears to constitute a relatively mild stressor (or even non-stressor), arguably similar to what has been reported for cognitive testing previously 30 . Importantly, the pattern of cortisol change suggests that the physiological stress was not equivalent in the four interventions, which means that general stress in response to the test situation (e.g. blood sampling) is unlikely to account for the gradual increases observed for mBDNF and pro-BDNF. However, since the study protocol did not include a passive control group (no intervention), we cannot exclude the possibility that the gradual mBDNF and pro-BDNF increases were caused by factors other than the interventions themselves. Taken together, plasma concentrations of mBDNF, pro-BDNF and cortisol displayed qualitatively different patterns of acute change under the same conditions of physical exercise and cognitive engagement, suggesting interventiongeneral increases in markers of neuroplasticity (mBDNF, pro-BDNF) and exercise-specific increases in markers of physiological stress (cortisol). The second aim of the investigation was to test a set of hypotheses pertaining to associations between rest levels and acute changes in mBDNF and cortisol, and between mBDNF and pro-BDNF. Consistent with the hypothesis and with previous findings in older adults, mBDNF and pro-BDNF were positively associated at rest 31 . Contrary to the hypotheses, however, no evidence was found for an association between parallel acute changes in mBDNF and cortisol, between changes in mBDNF and cortisol at rest, nor between mBDNF and cortisol at rest. As such, the results are inconsistent with a functional relationship between mBDNF and cortisol, where one inflicts change on the other 8 . Similarly, no evidence was found of an association between acute changes in mBDNF and pro-BDNF, contradicting a functional relationship also between these biomarkers. Thus, whilst acute changes in mBDNF, pro-BDNF and cortisol evidently occur in parallel, they appear to be unfolding independently, suggesting distinct origins.
When interpreting results above, it is important to consider the narrow set of circumstances that the present investigation provided. The acute interventions, comprising aerobic exercise of moderate intensity and/or cognitive training targeting working memory, reflect a very special set of circumstances that may or may not be representative of how the studied biomarkers co-vary under other experimental or more ecological conditions. Another important consideration concerns the limitations in how biomarker change was assessed and measured. Whilst AUC enabled measurement of acute biomarker changes across the entire session, capturing a general propensity for change, information regarding intervention timing was effectively lost. The low resolution at which acute change was measured, with only three timepoints, may also have limited the analytical sensitivity. The study did also not consider non-linear or time-lagged associations, which leaves the possibility for more complex patterns of biomarker co-variation to be discovered in future investigations. Conducting blood sampling in the morning, when for mBDNF and cortisol concentrations are declining, without information of time of awakening, reflect another important limitation.
The third aim of the study was to investigate whether acute changes in mBDNF, cortisol and pro-BDNF interact in their influence on cognitive training outcome. Contrary to the hypotheses, exercise-induced changes in mBDNF did not interact with parallel changes in cortisol or pro-BDNF, or with cortisol at rest, in its association with cognitive training outcome, when cognitive training was preceded by physical exercise. In other words, the beneficial effect of exercise-induced mBDNF for cognitive training outcome, when cognitive training was preceded by physical exercise, did not appear to be counteracted by temporally coupled changes in cortisol or pro-BDNF, or by cortisol at rest. However, an incidental finding revealed better cognitive performance when greater increases in mBDNF were coupled with greater increases in pro-BDNF, and only when physical exercise preceded cognitive training. Exploratory analyses revealed that this finding generalized to two additional cognitive composites also measuring updating working memory ability. In relation to the hypothesis, however, it is important to note that whilst the incidental finding did support an interaction between exercise-induced changes in mBDNF and pro-BDNF on cognitive performance, when physical exercise preceded cognitive training, it did not support a counteracting interaction. On the contrary, the nature of the interaction suggests that greater pro-BDNF increases may boost the beneficial effect of mBDNF on cognitive performance, which is difficult to reconcile with the role of pro-BDNF in suppressing neuroplastic processes 4,5 . However, since mBDNF is formed from the cleavage of pro-BDNF, greater plasma concentrations of pro-BDNF may simply reflect a larger pool from which mBDNF can be derived 32 . It is therefore conceivable that increases in pro-BDNF, when not overexpressed, can be positive for cognitive performance. However, in this context it should be emphasized that the incidental interaction was associated with cognitive performance level and not with performance change from pretest to posttest (i.e., cognitive training outcome), which contradicts a role in facilitating learning and therefore complicates an interpretation involving neuroplastic processes.
Exploratory analyses of relevance to the third study aim revealed indications of a potentially more general role for interactions among mBDNF, cortisol and pro-BDNF, for cognitive performance. In these analyses, AUC was used to capture acute biomarker changes across the entire session, which included both physical exercise and cognitive training, as opposed to change scores capturing acute change following physical activity specifically. As such, AUC reflected a more general measure of biomarker responsiveness to acute interventions, compared to the specific exercise-induced changes captured in the change scores. The AUC results showed that acute www.nature.com/scientificreports/ changes in mBDNF interacted with parallel changes in cortisol and in pro-BDNF, as well as with cortisol at rest, in its association with cognitive performance. More specifically, greater cognitive performance levels were associated with greater mBDNF increases coupled with lesser cortisol increases, as well as with greater mBDNF increases coupled with lower resting cortisol levels. When testing the generalizability of the finding beyond a single cognitive composite, the same result emerged for two other cognitive composites, also capturing the trained updating construct of working memory. These findings suggest that mBDNF and cortisol responses to acute interventions may indeed have interacting and opposing effects on cognitive performance, which is in line with previous proposals of an integrative system 8 . The exploratory results also showed that greater mBDNF increases coupled with greater pro-BDNF increases were associated with greater cognitive performance level, which is reminiscent of the incidental finding discussed above, and indicates that pro-BDNF and mBDNF may have multiplicable roles in their association with cognitive performance. As for the incidental findings, however, the biomarker interactions in the exploratory analyses emerged for general cognitive performance level, and not for change in cognitive performance from pretest to posttest. Additionally, the biomarker interactions did not differ depending on whether physical exercise preceded or followed cognitive training, suggesting that their positive associations with cognitive performance were not dependent on a particular timing and therefore may be more trait-like in nature. As such, the exploratory results give indication of an association between a particular combination of biomarker responsiveness and cognitive performance in healthy older adults, but they do not support a mechanism that involve learning via cognitive training.
In summary, the present study provided confirmatory support for a positive association between plasma mBDNF and pro-BDNF at rest, and exploratory support for a trait-like cognitive benefit of exhibiting greater mBDNF responsiveness to acute interventions when coupled with lesser cortisol responsiveness, greater pro-BDNF responsiveness, and lower cortisol at rest, in healthy older adults. Whilst unexpected, the results capture a unique set of findings that should motivate future research to test whether certain profiles of biomarker responsiveness may be associated with more preserved cognition in old age, informing the design of future personalized interventions for cognitive aging.

Data availability
Swedish data protection laws prohibit us from putting the data in the public domain, but data and/or analyses can be made available from the corresponding author on reasonable request (Jonna.nilsson@gih.se). For requests that involve specific and well-defined analyses that are in line with the original ethics approval, a data use agreement can be used to effectively transfer the confidentiality obligations of the institution at which the original research was conducted to the institution of the recipient of the data. www.nature.com/scientificreports/